DocumentCode :
3070482
Title :
Autoregressive Models for Spectral Analysis of Short Tandem Repeats in DNA Sequences
Author :
Zhou, Hongxia ; Yan, Hong
Author_Institution :
City Univ. of Hong Kong, Kowloon
Volume :
2
fYear :
2006
fDate :
8-11 Oct. 2006
Firstpage :
1286
Lastpage :
1290
Abstract :
A tandem repeat (TR) is a DNA sequence where a pattern of nucleotides is repeated a number of times. TRs cover more than ten percent of the human genome. They have been proven to play an important role in human diseases, regulation, and evolution. TRs vary for different individuals, so they are commonly used in human gene mapping, linkage studies, and forensic DNA fingerprinting analysis. In this paper, an efficient algorithm is presented for detecting TRs, especially short tandem repeats (STRs), in a DNA sequence. The algorithm, based on the autoregressive (AR) model, is to analyze the spectrum of the DNA sequences. Our algorithm can find TRs effectively and quickly. Furthermore, it is robust to mutations, deletions, and insertions. In comparison with the fast Fourier transform (FFT), our results show that the AR model based algorithm can provide more detailed qualitative information than the FFT when we analyze the spectrum of the STRs. Here, the methods and ideas underlying the algorithm are presented and the effectiveness of the algorithm on TRs is demonstrated.
Keywords :
DNA; autoregressive processes; biology computing; fast Fourier transforms; genetics; molecular biophysics; sequences; spectral analysis; DNA sequence; autoregressive model; fast Fourier transform; forensic DNA fingerprinting analysis; human gene mapping; spectral analysis; tandem repeat; Algorithm design and analysis; Bioinformatics; Couplings; DNA; Diseases; Forensics; Genomics; Humans; Sequences; Spectral analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
Type :
conf
DOI :
10.1109/ICSMC.2006.384892
Filename :
4274026
Link To Document :
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